In response to companies looking for more decentralized services with less IT overhead, Oracle has launched the Planning and Budgeting Cloud Service (PBCS). PBCS is a hosted version of the Oracle Hyperion Planning and Data Management/Integration (FDMEE) tools with a particular focus on a completely online-based interface. For additional information on PBCS, please click HERE.

From a functional perspective, this is an ideal situation: to have near-full capabilities of an on-premise solution without the infrastructure maintenance concerns. Practically, though, there are some holes to fill as Oracle perfects and grows the solution.

One of the main areas for concern has been the integration of data into and out of PBCS. Data Management (a version of FDMEE) is the recommended tool for loading flat file data into the system, while there is also the ability to load directly to Essbase with perfect files. Getting files out of the system, on the other hand, has not been so straightforward. Without access to the Essbase server, exporting files proves impractical. Companies often need data exports from Essbase for backups, integrations into other systems, or for review. PBCS does not seem to have a native method of being able to extract Level Zero (Lv0) data on a regular basis that could be easily copied out of the system and used elsewhere.

Despite this, the DATAEXPORT command still exists in the PBCS world. How, then, could it be used to get a needed file?

It actually begins as with a normal on-premise application by creating a Business Rule to do a data export. This can be done manually, but it is recommended to use the System Template to make sure everything is set up perfectly.

When setting up the location to export the file to, it should be set up as:

“/u03/lcm/[File_Name.txt]”

When this is done, a user can then navigate over to the Inbox/Outbox Explorer and see the file in there:

And that is really all there is to it! With a business rule in place, the entire process can be automated using EPMAutomate (EPMAutomate and recommendations for an automation engine/methodology will be discussed in a later post) and a batch scripting client to do a process that:

Deletes the old file

Runs the business rule to do the data export

Copy the file off of PBCS and to a local location

Push the file to any other needed location

The one important thing to note is that as of PBCS 11.1.2.3.606 (April 2015 patch), all files in the Inbox/Outbox Explorer — along with any files in Application Management (LCM) — that are older than two months will be automatically deleted. As such, if these files are being kept for archive purposes, they must be backed up offline in order to be preserved.

In the 11.1.2.3 release of the EPM stack, Oracle introduced Financial Data Quality Management, Enterprise Edition, or FDMEE. FDMEE was not entirely a new product but rather a rebranding of ERP Integrator (ERPi), which was released in 11.1.1.3. FDMEE actually represents the convergence of two products – FDM (now known as FDM Classic) and ERPi – and represents the best of both products. Besides the obvious changes – a new user interface (UI) that is integrated into Workspace, leveraging Oracle Data Integrator (ODI) as its data engine and direct integration to many Oracle and SAP ERP source systems – FDMEE introduced one rather significant change: Jython as its scripting language.

For organizations that have a significant investment in FDM Classic, a new scripting language likely represents one of the most daunting changes in the new data management tool known as FDMEE. Before we continue, let’s briefly talk about scripting in FDMEE. Customers face a choice with FDMEE scripting – VBScript or Jython. I have spoken with a number of customers that have asked, “Can’t I just stick with VBScript because it’s very similar to the FDM scripting, which was basically VBScript.” The technical answer is, in most cases, yes, you likely could. The more thought-out answer is, “Have you considered what you are giving up by sticking with VBScript?” Well, that really isn’t an answer, is it?

Let’s take a moment to understand why I ask that question. Let’s consider at a high level the differences in these two languages. For Wikipedia: VBScript (Visual Basic Scripting Edition) is an Active Scripting language developed by Microsoft that is modeled on Visual Basic. It is designed as a “lightweight” language with a fast interpreter for use in a wide variety of Microsoft environments.Jython, successor of JPython, is an implementation of the Python programming language written in Java.

Take a moment to consider the Enterprise Performance Management (EPM) stack at Oracle. Have you noticed any trends over the past two to three years? In 11.1.2.2, Oracle rewrote the UI for HFM using the Oracle ADF framework. In 11.1.2.3, Oracle removed all but the most basic functionality from the HFM Win32 client. In 11.1.2.4, HFM is planned to be platform agnostic meaning it can run on virtually any operating system including Linux and UNIX. Have you heard about this nifty new appliance called Exalytics? My point in this trip down memory lane is that Oracle is clearly moving away from any reliance on Microsoft technology in its product stack. Any time I have said this, the question inevitably is asked: “Do you think we’ll still be able to run EPM on Windows servers?” My answer is a resounding YES. Oracle may not be the biggest fan of integrating Microsoft technology into its software solutions, but they are smart enough to understand that failing to support Windows as a server platform would lock them out of too large of a share of the market. So breathe easily; I don’t see Oracle producing EPM software that won’t be able to be deployed on Windows servers.

The EPM stack is moving toward becoming fully platform agnostic. Exalytics is, for those of you who are not familiar, an in-memory Linux or Solaris machine that delivers extreme performance for Business Intelligence and Enterprise Performance Management applications. At a very high level, these machines have an extraordinary amount of memory (RAM) that allows the entire database to be brought into memory. The result is incredible performance gains particularly for large applications.

There are at least two constants with technology. First, data continues to grow. The demand for more data to support business decisions is no exception. The other constant is that hardware continually improves while the cost always drops. I can’t envision Exalytics being an exception this. Today’s Exalytics machines often cost six figures, and that may not be an expense your organization can justify. However, in two to five years, your organization may require an Exalytics machine, and it may well be an expense you can justify.

Given this bit of background, let’s talk about why I firmly believe Jython is the better choice for your FDMEE application. As the EPM stack moves toward being platform agnostic, I believe that support for supporting Microsoft technologies such as VBScript will slowly diminish. The application programming interface (API) will continue to be enriched for the Jython language set, while the API for VBScript will be less robust. Please keep in mind that this is just my prediction at this point. But Oracle is no different than any other organization that undertakes technology projects. They employ the same three levers that every project does – scope, time, and budget. As a customer of EPM, you have noticed the speed at which new releases have been deployed. To continue to support two sets of APIs within these accelerated development timelines will require one of the remaining levers to be “pulled.”

That leaves us the scope and budget levers. To maintain complete parity (scope) with a fixed timeline, the remaining lever is budget. Budget for any technology project is heavily correlated to people/projects. Add more people to the project, and the cost goes up. As I said before, Oracle is no different than any other organization. Project costs must be justified. So the development head of FDMEE would need to justify to his senior management the need to add additional resources to support having two sets of APIs – one of which is specifically for Microsoft technologies. One can imagine how that conversation might go.

So we’re left with the scope lever. There are two APIs – one to support Jython (JAVA on Python) and a second to support VBScript (a Microsoft technology). Let’s not forget that Oracle owns JAVA. Which do you think wins? I hope that I have built a case to support my previous conjecture about the expected richness of the Jython API vs. the VBScript API.

Let’s say you believe my above predication is wrong. That’s OK. Let’s focus on one key difference in these technologies – error handling. Throughout my years of developing scripts for FDM Classic, the reoccurring theme I heard from customers was when a process fails, can the system alert me? The technical answer is, most likely. The practical answer is no. While in a VBScript routine I can leverage the On Error Resume Next in conjunction with If Err.Number = 0, I would need to do this after every line of code and that is simply not realistic. The best solution I have found is writing scripting operations to a log file that can then be reviewed to identify the point at which a script fails. While this approach has helped, it’s not nearly as elegant as true error handling like what is available in Jython.

Jython provides error handling through the use of the Except keyword. If you have ever written (not recorded) Excel VBA macros, you may be familiar with this functionality. In VBA, you would code On Error Goto ErrHandler and then have code within an ErrHandler section of the script that performs some operation in the event of an error. Within Jython, there is a similar, albeit more robust, concept with the Try – except keywords. For example:

In the above example, the Except clause is used to handle division by zero. With Jython, you can have multiple Except clauses to handle different anticipated failures in a process. Likewise you can have a catch-all (finally) clause to handle any unexpected failures. A key functionality with the Except clause is the ability to capture the line in the script that caused the failure. This is a key improvement over VBScript.

We could continue to delve further into the technical details of why Jython is a more robust language, but when I think about this conversation in context of, “Why do I want to use Jython instead of VBScript for my application?” I think the above arguments are compelling on their own. If you are interested in learning more about Jython scripting for FDMEE, please attend my session at Kscope14:

As mentioned in the previous post, Dynamic Report Grouping with Oracle BI Publisher, Edgewater Ranzal is working with a client to convert XML Publisher reports to BI Publisher reports. As part of Ranzal’s initiative, we began looking for opportunities to improve the user interface as well as create a standard methodology that report developers could utilize in the future. One of the initial areas we focused on was to improve the prompting feature. To this effort, we concentrated on:

Presenting prompts to the user within the BI Publisher tool

The displaying of user-entered prompt values within the report

Creating a methodology of implementation for report developers.

As expected, many of the reports had time prompts (date, period, or year), but the existing reports did not have default prompt values. Although it is not published in any Oracle documentation we have seen, Oracle offers five functions that can be inserted into the Default Value option of the parameter:

*Note that you also have to set the Data Type to Date for these parameters.

Simple numeric mathematical calculations can be performed with these functions to add some flexibility. For instance, the previous day’s date would be displayed as

{$SYSDATE() – 1$}

By using these functions in conjunction with the Date String Format in the parameter options section, a variety of date value defaults can be displayed in the prompting section of the report. The following table is a sample of the prompts, Default Value, and Date Format Strings that were deployed at the client:

It is very important to understand that, regardless of the Date Format String settings, the actual value used in the date functions is the full date string and an optional numeric number added or subtracted that represents days. For instance, if the Default Value is set as {$FIRST_DAY_OF_YEAR() + 1$} (first day of year plus one) and the Date Format String is set to MM, the user would still see 01 as the default value because the actual value generated (and then converted to the month number) is 20XX-01-02T00:00:00.000+HH:00 (Jan 2, 20XX).

Because the optional numeric value used in the function refers only to days, and no logic can be written into the Default Value function, there is a natural limitation that prohibits generating anything beyond a period and/or year plus or minus one. For instance, if a client wants a prompt default value for two years ago, logic cannot be written to determine if the current year or previous year was a leap year and conclude whether to subtract 365 x 2 = 730 or 366 x 2 = 732 from the first day of year function (or system date function, depending on your preference).

Understandably, this problem would only occur two days every four years (December 31st of both a leap year and the year following a leap year); however, extrapolating from this logic is evidence of the difficultly in going back two or more months from any date function because of the variable numbers in a month. We observed an even more complicated version of this issue when the client wanted to have the default values for a period range equal to the previous period (i.e. during Q3, From Period defaults to 04 and To Period defaults to 06). Depending on the current period, the From Period needs to default from three to five periods ago and the To Period needs to default from one to three periods ago. Further exacerbating this problem was the year prompt that, during Q1, needs a default value of the previous year.

The final piece of the puzzle when using any parameters with the date data type is realizing that the bind value passed to your data model is the full date/time string. Our client exclusively used SQL in their data models; therefore, it was only a matter of using Oracle SQL’s native TO_CHAR function to convert the date/time string to a relationally comparable value as such:

The Ranzal team then looked to streamline and simplify interaction between parameters, parameter input requirement evaluation, and the RTF templates. The client’s reports had up to twelve parameters that required user input, and they used XLST logic to evaluate whether or not users had supplied values. As mentioned in previous posts, XLST is not a robust language as it relates to logical evaluations; after all, XLST was designed to consume XML documents and output new documents (in this case, RTF based reports). Because of these limitations, the initial RTF templates used the following logic (white space added for clarity):

Using this method, each parameter is evaluated until a null value is found, and then the remaining parameters are evaluated for a null value. When the XLST consumes the XML, each required parameter that the user has not entered a value for results in an additional warning line message. From a developer point of view, each additional required parameter requires the creation of additional lines of code. While the example above only has four required parameters, reports with many required parameters become quite convoluted and difficult to maintain.

Ranzal again turned to the logic processing capabilities of Oracle SQL. Within the data model, we created a new data set to create a parameter status (named PARAM_STAT) to look at the bind values passed by the BI Publisher parameters. We came up with the following SQL template to generate a more succinct warning message within the column value PARAM_STAT (note that n denotes the number of required report parameters):

There is an argument for creating a SQL statement that concatenates all missing parameter names with a comma and then uses logic to correct the punctuation; however, we felt that from a reusability standpoint, it would be best to compartmentalize the statement using the WITH TABLE1 statement. Using the above SQL template, report developers merely have to update the following lines:

Using the example above with the required parameters for year, period, business unit, and ledger, the following SQL statement was generated:

Using this parameter status value results in a much more succinct XLST template that needs only to evaluate whether PARAM_STAT has a value (white space added for clarity):

The client has hundreds of BI Publisher reports and plans to continue to develop additional reports as their Oracle Business Intelligence platform becomes the standard reporting tool. By using the SQL template along with the simplified RTF template, the real work becomes creating the table, pivot table, or chart within the RTF template. Fortunately, the Ranzal team was able to create an Excel-based VBA macro that automates the generation of the majority of the client’s templates. We will discuss this tool in a later post.

These two examples demonstrate the Ranzal team’s commitment to taking a proactive stance to examining current processes and looking for opportunities for improvement. As we worked through the technical details of this implementation, we carefully balanced the idea of a user-centered experience against the often competing need for a simplified methodology and process for report developers. To accomplish the latter, we went through several phases of technical refinement, demonstrated the process to developers, and provided thorough documentation. This ensures that when the time comes to turn the maintenance of these reports over to the client, there is a complete knowledge transfer as well.

Edgewater Ranzal is working with a client to convert XML Publisher and nVision reports to BI Publisher as part of a larger initiative to consolidate reporting under the Oracle Business Intelligence solution. The client currently does not use the BI Publisher Layout Editor, but rather relies on RTF templates to display results to the user. One nVision report in particular presented a challenge because of the grouping requirements.

The report requires users to enter an Account range, and the resulting tables need to be grouped by individual accounts. There are also seven optional wildcard prompts, including Product and Department. If the optional prompts are left blank, the results need only to be grouped by the individual accounts; however, if values are entered for the optional prompts, the subsequent results need to be grouped by all resulting unique combinations for the prompts entered. For instance, if the user enters 10000 to 20000 for the account range and all departments beginning with 10, an example report may be:

Sample Data Only

If the user adds the wildcard criteria (%) for the optional prompt Product, the results are further grouped by Product as such:

Sample Data Only

One approach to meet the client’s needs for this particular nVision report is to use the grouping feature in the Microsoft Word BI Publisher Table Wizard. To fulfill the requirement of grouping only when users enter values in the optional prompts, the XLST statements that create groupings can be wrapped in IF statements that evaluate the prompts for null entries. For example, Department and Product can be evaluated as such (note that all prompts begin with PRM):

This approach has two drawbacks: First, after adding the additional evaluations for the other five optional prompts, the XLST within the RTF template becomes quite convoluted. The second, and more limiting factor, is that the IF statements to end the “group by” statements (below the table template) result in either a non-functioning report or incorrect groupings.

A second and more viable option is to use the Data Model to leverage Oracle SQL which has more robust logic evaluation capabilities than XLST. To meet the client’s needs, an additional column was added to evaluate user prompt values (note that all prompt variables begin with PRM, and CHR(13) returns a carriage return):

This column evaluates each optional prompt for a value and, if the user has made an entry, concatenates the common name (i.e. Department and Product) with the value of the respective row and a carriage return; otherwise, a null value is returned. The Microsoft Word BI Publisher Table Wizard feature is then used to generate the XLST needed to group the table by the new column GRPOPT in a more succinct fashion:

By leveraging the Data Model SQL rather than XLST within the RTF template, Ranzal recreated this nVision report while maintaining the sort of dynamic capabilities normally seen in Oracle Business Intelligence Answers. The additional SQL statements add no overhead to the BI Publisher report, and the report runs as fast as or faster than, the corresponding nVision report. The delivery of this report opens up new reporting possibilities for the client, and it reinforces Ranzal’s expertise in the Oracle Business Intelligence tool set.

There are times when you do not have an option of using FDM to do large data mapping exercises prior to loading data into Essbase. There are many techniques for handling large amounts of data mappings in Essbase, I have used the technique oultined here several times for large mappings and it continues to exceed my expectations from a performance and repeatability perspective.

Typically, without FDM or some other ETL process, we would simply use an Essbase load rule to do a “mapping” or a replace. However, there are those times when you need to do a mapping based on multiple members. For example, if account = x and cost center = y then change account to z.

Let’s first start with the dimensionality that is in play based on the example below: Time, Scenario, Type, NOU, Account, Total Hospital, and Charge Code

Dimension

Type

Members in
Dimension

Members
Stored

Time

Dense

395

380

Scenario

Dense

13

6

Type

Sparse

4

4

NOU

Sparse

25

18

Account

Sparse

888

454

Total Hospital

Sparse

5523

2103

Charge Code

Sparse

39385

39385

You then need to be able to identify the logic of where the mapping takes place. I will want to keep the mapping data segregated from all other data so I will load this to a Mapping scenario (Act_Map). I load a value of ‘1’ to the appropriate intersection, always level0. Since the mapping applies to all Period detail I will load to a BegBalance member. The client will then update this mapping file from a go forward basis based on new mapping combinations.

Here is what it looks like when you do a retrieve. So for 4410CC->2600427->IP->67->SVM there is a value of 1 and for 4410CC->2600435->IP->67->SVM as well.

The next step in the process is to load the actual data that ultimately needs to be mapped. I will load this data based on the detail and dimensionality I have, again at level0. In my experience, the data is missing a level of detail (GL account for project based planning, Unit/Stat for charge master detail, etc.). So this data gets loaded to specific “No_Dimension” member via a load rule or a generic member. Again, I load this data to a separate scenario as well (Act_Load).

In the example below you will see I am loading Account detail (67 & 68 in the above screenshot) to the Stat_Load member. The data comes across missing the account detail.

The final step is to calculate the Actuals scenario based on the two scenarios above. You will see that after we run the calculation, Current Yr Actuals is calculated correctly in that the data resides where it should reside.

Keeping all the data segregated in different scenarios allows you to easily clear data should anything be wrong with one of the loads, thereby keeping the other datasets intact. This process runs on the entire year in less than 2 minutes and not only performs the calculation but also does an aggregation for the Current Yr Actuals.

Welcome to the first installment of our new Hyperion Strategic Finance (HSF) blog series. Edgewater Ranzal’s HSF team has been working closely with Ranzal’s other Hyperion practices (HFM, FDM, Planning/Essbase etc.) to hone in on how HSF can be utilized to its full potential in accordance with the other product offerings. As part of that process we felt it was important to start a dialogue (blog) to share some of our insights on various topics ranging from new product release info to cutting edge integration best practices. We are hoping this series will be a good resource for you and your organization on your HSF journey.

Given the major changes to HSF in the 11.1.2.2 release, and the exciting product roadmap ahead of us, I thought it would be good to start the series by discussing “The New Era of Hyperion Strategic Finance.”

So…What’s new?

With the 11.1.2.2 release comes probably the most significant change to the product since it was acquired by Hyperion. A shift in the user interface from a traditional thick client to an Excel based Smart View Add-in is at the core of the change. The enhancement enables the end user to perform the majority of HSF modeling activities directly in an Excel workbook. With this change, the legacy reporting in the HSF client has been REPLACEDwith Excel reporting via Smart View. This means that those who choose to implement 11.1.2.2 will be required to use the Smart View based reporting and/or export the data to an external database (i.e. Essbase) to utilize other reporting tools (i.e. Financial Reports, OBIEE etc.). For any current HSF users looking to upgrade, it is important to note that the process of upgrading to 11.1.2.2 automatically converts existing HSF reports into the Smart View format, however, existing charts/graphs will need to be rebuilt and some formatting issues have been identified which may require some re-work. While this does introduce a big change for end users, it also presents a great opportunity by opening up native Excel functionality like allowing the use of Excel graphing, conditional formatting, highlight sums, and the group / ungroup data feature etc. To view the full list of new features you can look through the 11.1.2.2 Read me, available here.

Why make the change?

Some existing clients have asked me why this change was made in the first place. The answer is really two-fold:

1. Tighter Integration with Hyperion Planning: If there has been one consistent theme throughout all of my meetings/conversations with Oracle’s HSF/Planning development team it has been a desire to continuously improve the integration between Hyperion Planning and HSF. The integration I’m referring to doesn’t stop at data, but also includes seamlessly integrating the end user experience. Everything from selling the tools as a combined solution (i.e. bundled pricing) to having both HSF and Planning users interact with the tool in a similar manner (i.e. Smart View) have been or will be addressed. Below I will outline some additional roadmap items that are planned that will continue this theme.

2. Reporting: All legacy HSF users that have spent time creating, formatting, and modifying HSF reports are well aware that reporting has NOT been an area of strength previous to 11.1.2.2. Both Oracle and our implementation team consistently receive requests to have HSF reporting operate “more like Excel.” This move is a direct response to those requests, and it is definitely a big step in the right direction.

Current Challenges:

As with any major change / new release there are going to be some growing pains and the 11.1.2.2 release of HSF is no different. We have been working closely with Oracle over the past couple of months to identify any issues, make recommendations, and test fixes that have been applied. The main point I want to make clear is that from a functional perspective the tool has the EXACT same capabilities. You are simply changing the way you do things, not what can be done. There is a bit of a learning curve to understand the new menu bar, short cut keys etc…but in general it still functions much like its predecessor with the added benefit of the Excel look and feel.

A couple of things to look out for if you will be implementing AND going live prior to the 11.1.2.3 release:

1. Issues with large numbers of active reports: We have experienced some performance issues when working with a file that has numerous reports (standard or freestyle) open at once. This includes reduced speed of the check out / in process, flickering upon calc/refresh, and occasional freezing of the application. Currently, the product seems to work more seamlessly when working with just the accounts tab or 1-2 reports, however, fixing this is at the top of Oracle’s priority list and we expect it to be addressed sooner rather than later.

2. Renaming of Time Periods: You want to avoid renaming the default time periods in the entities (i.e. Changing 2013 to FY13). In the current release this can cause some calculation issues in system regarding the funding routine. Again, this has been identified by Oracle and is expected to be resolved in the next patch set or release.

3. Smart View Parity: There are some features that are not currently in the Smart View interface which may require users to revert back to the old HSF client. Some of these features include the debt/depr schedulers, ECM/ACM etc. This means that the end user may have to jump between interfaces in certain instances. The good news is that these features are expected to be added to the Smart View functionality in the next release (11.1.2.3) and can still be utilized in the traditional client if need be. To see a full list of these items look to the 11.1.2.3 roadmap column below.

4. With the change in the technology, come some changes to the infrastructure component, so it is important to discuss these requirements with your technical team to diagnose hardware and software needs before moving forward. It is also important to note that the upcoming release of 11.1.2.3 will NOT be backward compatible with 11.1.2.2. So, if you have a multiproduct implementation with integration components you would need to upgrade the entire suite.

Product Direction / Road Map

The above picture is a snap shot of the HSF roadmap given to me by the Oracle product team. You can see the current release (as of this blog post) on the far left, calendar year 2013’s scheduled release (11.1.2.3) in the middle, and the subsequent releases on the far right. The focus this year is to truly stabilize the Smart View integration and incorporate all of the standard features of the thick client into the Smart View interface. The exciting part of this is how the changes in 11.1.2.2 have set up the product for even more advancement in the future. Post 11.1.2.3, a lot of the heavy lifting for HSF’s major changes will be complete. This will allow the team to focus on true feature enhancements like adding a monthly depreciation scheduler or addressing the concept of parent level scenario modeling (possibly an idea for a future blog post!). In addition, if you look at the future direction, in the Enterprise Readiness section, you will see items such as LRP Integration to Planning, Automated Data Loads, DRM support etc…This represents a future state which allows a user to manage both data and metadata in a consistent manner between HSF, Planning, and Essbase. Imagine a world where you can have one excel worksheet open with your HSF model and another with a LIVE connection to an HSF reporting cube (via Essbase) for Ad-hoc purposes! Not only that but a world where the Essbase cube is automatically updated as you make changes to the HSF model, meaning no manual metadata management between applications or tedious mappings that need to be maintained. This type of enhancement truly empowers the user to focus on the modeling aspects of HSF while allowing Essbase to shine for management reporting – truly using the right tool for the right job.

Our Recommendation

Overall we are very excited about the direction Oracle is heading with HSF. The Smart View capability in 11.1.2.2 is really just the first step in what we see as a continued effort to make the product better for its users. With that in mind, we have begun multiple 11.1.2.2 implementations, however, it is understood in all cases that there will be some issues to work through and there are no pending deadlines where these issues could put the project success at risk. In fact, the Go Live dates are not expected to occur until a time when we believe 11.1.2.3 and / or an 11.1.2.2 patch set will be available. Given that, we do recommend that all new HSF clients seriously considering starting with v11.1.2.2 while taking note of the challenges mentioned above. Initially this approach eliminates the need for your end users to learn two different user interfaces. Additionally, if you are willing to give feedback, as an 11.1.2.2 client you will definitely have the ear of the Oracle team as it pertains to resolving any existing product issues, as well as requesting new enhancements for the future. Oracle is very eager to make this release a success and they truly value any input early adopters can provide. So if you have the patience to work through some bumps in the road, and the time to resolve the issues you may encounter, I would definitely encourage giving the 11.1.2.2 release serious consideration.

I hope you found this information helpful. We look forward to coming out with many more in the future. In that vein, if you have any ideas / request for blog topics please feel free to leave them in the comments section or reach out to me directly at rmeester@ranzal.com and we will make sure to address them in future posts.

About the Author

Ryan Meester is a Practice Director for the Strategic Planning Practice at Edgewater Ranzal. His first encounter with HSF dates back to 2004 as a Consultant with Hyperion in the HSF practice. After three years in that capacity, leading projects and assisting with business development efforts, Ryan co-founded Meridian Consulting International with two of his Hyperion colleagues, Andrew Starks and Ricardo Rasche. At Meridian, Ryan, Andrew, and Ricardo focused exclusively on HSF implementation services until Meridian was acquired by Edgewater Ranzal in May of 2010. This was a strategic acquisition for both Meridian and Ranzal. Both organizations were seeing more and more multiproduct implementations which required a broader EPM focus. The acquisition effectively rounded out Ranzal’s EPM service offering by adding HSF expertise to their repertoire.

• Standard definitions and metrics
• The understanding of how users will consume data and interact with the system

To effectively create reports, make sure to follow these key best practices:

1. Reduce the data presented by focusing on the important information. For example, rather than showing two lines for revenue actuals and revenue budget, try showing one for the difference. Users can identify trends much more quickly when there are fewer objects to focus on.

2. Concentrate on important data and consolidate it into chunks. If you have two charts, use the same color for revenue on both of them. This makes it easier to interpret and see trends between them

3. Remove non-data items, especially the images, unnecessary lines and graphics. This helps the user focus on the actual data, so they can see trends and information rather than clutter.

Here is an example of two reports with the same data. The first provides a table with various colors, bold fonts and line. The second report highlights the important areas/regions. Your eyes are immediately drawn to those areas needing attention. Table two allows the user to draw accurate conclusions more effectively and in a much shorter timeframe.

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